Experts from the industry highlight the important role that artificial intelligence plays in improving the operational efficiency of IoT infrastructures, from predictive maintenance through logistics to optimization of processes. IoTSWC 2018 includes in this article the keys that are marking the current relationship between IA and IoT.
The main objective of applying Artificial Intelligence (AI) (*) to the Internet of Things (IoT) infrastructures is to add an additional and transversal layer of intelligence throughout the IoT framework. The scientist and Global Managing Director of Technology Labs of Accenture, Edy Liongosari, points out that AI is used, first and foremost, to create sensors that self-calibrate, or self-recover when the IoT network or an individual sensor fails, identifying them by proximity or, even, by creating a new type of ‘virtual sensors’ that use artificial vision MRI (Magnetic Resonance Imaging), a non-invasive image visualization technique that is used, for example, to detect cancer cells and that reproduces three-dimensional representations .
In the highest stratum of the IoT infrastructure, the application, Liongosari emphasizes that artificial intelligence provides new functions related to «the predictability of future events, maintenance tasks or security issues». In this sense, the director of Accenture points out some examples: «Thanks to the AI it is possible to identify who is authorized to use a certain equipment and their degree of preparation; offer context-based services with additional capabilities for more intensive uses; optimize the operation of the supply chain through its rethinking or reprogramming due to causes that interrupt its operation; or get to interact with the user from the recognition of their emotional state by a combination of gestures, voice and facial gestures in order to understand their needs in a specific context «.
In order to understand how AI helps all types of industries to add more efficiency to their IoT infrastructures, it is useful to go back a little in time to see how the use of IT has evolved in the industrial environment. Wael William Diab, Senior Director of Huawei, member of the Industrial Internet Consortium (IIC), expert in artificial intelligence and regular lecturer at the IoT Solutions World Congress of Fira de Barcelona, recalls that, at the beginning, information technologies applied to were seen as tools that increased efficiency within organizations.
«After the IT were considered essential elements when measuring the performance of an activity comparing them with other KPIs established by the management team. If we stick to the scope of the IoT, IT has integrated more deeply into the chain of management to reach areas related to decision-making, even in more traditional industries that had no relationship with IT in the past » says Diab.
In his opinion, artificial intelligence today drives a new change in IT «that provides the knowledge that has to serve to establish future objectives and KPI elements. In other words: the AI has managed to get a seat at the management table, adding its voice to where the organization should reach by way of knowledge «, says the expert.
IA, IoT and Analytics: winning trident
From the technological point of view, it is important to remember that artificial intelligence is composed of a subset of technologies such as machine learning (ML) and deep learning (DL). «Artificial intelligence, the internet of things and analytics make up three aspects of the same reality,» Huawei official Wael William Diab points out. «While IoT focuses on sensor networks that generate data, the processes of analytics are limited to the analysis of such data with the aim of creating value, while artificial intelligence enables the generation of knowledge and predictability from such value data «.
Both Liongosari and Diab coincide when affirming that thanks to the extensive applicability of the AI it is possible to integrate data analytics mechanisms in practically all types of industrial sectors. However, Liongosari warns that the most important value that can be extracted from AI depends largely on the applications. «The AI has a very important role in the improvement of operational efficiency, which is a large part of the current implementations of the industrial internet of things from predictive maintenance, through logistics to the optimization of processes.»
Studies on the impact of AI on predictive maintenance, such as the one carried out by the firm Anodot, highlight that this possibility will save organizations between 240,000 and 630,000 million dollars in 2025 thanks to the reduction of downtime and related expenses. maintenance processes. At the other extreme, predictive maintenance has the ability to generate new business models, new sales channels, better services and a superior user experience. In this sense, Michelin’s ‘Tire-as-a-service’ strategy is an example of transforming the business model of a traditional industry through IoT and IA.
In aspects related to the application of predictive analytics in different industries, Diab recommends using the term «industrial» in a similar way to how the Industrial Internet Consortium (IIC) does when it comes to covering different sectors, instead of focusing only in the manufacturing processes. «IIC has recently published the Industrial IoT Analytics Framework (IIAF) study that helps and helps industrial leaders and developers of analytical systems add value to the business by making decisions related to development, documentation, communication and the deployment of IoT infrastructure. «
In terms related to the emergence of new standards in the section of predictive analytics, the ISO international standardization organization has established the ISO / IEC JTC 1 / SC 42 in IA, the first standard that seeks to encompass the artificial intelligence technological ecosystem in its entirety, and whose creation committee has proposed Wael William Diab as Chairman in this category.
The standardization of artificial intelligence will undoubtedly benefit the industry and will lead to a new era of growth as there are many companies that will make significant investments in AI solutions. This regulation guarantees that they will be able to continue working and evolving in this field during the next years.